光谱学与光谱分析 |
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Value of Auto-Fluorescence Spectrum Combined with Tumor Markers in Diagnosis of Lung Cancer |
WU Yong-jun,HAO Yan-hong,WU Wei-chao,WU Yi-ming* |
College of Public Health, Zhengzhou University,Zhengzhou 450001, China |
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Abstract To improve the diagnostic efficiency of cancer, serum fluorescence spectrum combined with tumor marker groups was proved more powerful, especially when used with mathematical evaluation model, that is, artificial neural network (ANN) modeling. ANN modeling is very suitable for the discrimination of lung cancer. ANN has evident superiority in solving nonlinear, multi-parameter and uncertain complicated problems. In the present paper, serum fluorescence spectrum was applied to study the difference among normal, benign and malignant groups and develop the relevant method of determination. On the other hand, combined with tumor markers, CEA, NSE, SCC-Ag, CYFRA21-1 and p16 methylation, artificial neural network and Fisher linear discriminatory analysis were used to develop the prediction models of diagnosis of lung cancer, and compared by ROC. It was shown that the result of the fluorescence spectrum combined with tumor markers based on ANN model is superior to that of the fluorescence spectrum ANN model. The performance of ANN model is superior to that of Fisher linear discriminatory analysis.
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Received: 2008-11-06
Accepted: 2009-02-08
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Corresponding Authors:
WU Yi-ming
E-mail: wuym@zzu.edu.cn
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[1] Masilamani V, Al-Zhrani K, Al-Salhi M, et al. J. of Luminescence, 2004, 109: 143. [2] WU Yong-jun, WU Yi-ming, ZHANG Zhen-zhong, et al(吴拥军,吴逸明,张振中,等). Journal of Practical Oncology(实用肿瘤学杂志),2002,17(5):317. [3] De Fraipont F, Moro-Sibilot D, Michelland S, et al. Lung Cancer, 2005, 50(2): 199. [4] LI Li-ming(李立明). Epidemiology(流行病学). Beijing: People’s Medical Publishing House(北京:人民卫生出版社), 2004. 289. [5] Sakaguchi I, Katabuchi H, Okamura H. Nippon Rinsho., 2004, 62(10): 607. [6] WANG Wei, LIU Wen-kai(王 卫, 刘文凯). Journal of Instrumental Analysis(分析测试学报), 2005, 24(4): 80. [7] CHU Xiao-li, YUAN Hong-fu, LU Wan-zhen(褚小立, 袁洪福, 陆婉珍). Chinese Journal of Analytical Chemistry(分析化学),2000, 28(4): 421. [8] Zhang Q Q, Lei S H, Wang X L, et al. Spectrochimica Acta A, 2006, 63(2): 361. [9] ZHANG Yi-min, XIA Wen-jin, MAO Cai-ping, et al(张毅敏,夏文进,毛彩萍,等). China Oncology(中国癌症杂志),2008, 18(4): 306. [10] Young M T, Blanchard S M, White M W, et al. Computers and Biomedical Research, 2000, 33(1): 43. [11] WANG Jia-liang(王家良). National Medical Journal of China(中华医学杂志), 1998, 78 (12): 941. [12] Copas J B, Corabitt P. Biometrika, 2002, 89(2): 315. [13] Carsten Stephan, Henning Cammann, Hellmuth-A Meyer, at al. Cancer Letters, 2007, 249: 18. |
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